The success of Variable Rate Application (VRA) techniques is closely linked to the algorithm used to calculate the different fertilizer rates. In this study, we proposed an algorithm based on the integration between some estimated agronomic inputs and crop radiometric data acquired by using a multispectral sensor. Generally, VRA algorithms are evaluated by comparing the yields, but they can often be affected by factors acting in the final phase of the crop cycle and not dependent on the fertilization treatments. Therefore, we decided to compare our algorithm (ALG) versus the traditional application of fertilizer (TRD) by evaluating the crop growth 1.5 months after the fertilization time. The algorithm was tested on a sorghum crop under organic farming, managed with or without manure. The saving of N obtained with ALG was equal to 14 and 5 kg ha^− 1 (-14 and − 10% for the non-manure and fertilized treatments, respectively). The NDVI values acquired after fertilization showed a remarkable reduction of relative standard deviation for ALG system (from 22 to 9% and from 34 to 14% for manured and not manured, respectively), which was not found for TRD system (from 16 to 17% and from 29 to 18% for manured and not manured, respectively). The above ground biomass produced was statistically equivalent for the two systems in the manured plots and significant higher for ALG in not-manured plots (+ 0.74 t ha^− 1 of dm, equal to + 23%). Finally, the indices calculated to evaluate the Nitrogen Use Efficiency (NUE) were consistently better in the ALG theses.

In 2013, a pilot experimental field of about 15 ha was set up within the basin of Lake Massaciuccoli (Tuscany, Italy) in order to compare different management strategies—a paludicultural system (PCS), a constructed wetland system (CWS), a nearly-natural wetland system (NWS)—for peatland restoration after almost a century of drainage-based agricultural use (CS). After five years, changes in peat soil quality were investigated from a chemical, biochemical, and ecoenzymatic perspective. The soil in CS was mainly characterized by oxidant conditions, higher content of overall microbial activity, low levels of easily available phosphorus for vegetation, and medium total carbon content ranging from 25.0% to 30.7%. In PCS, the levels of total carbon and the content of bioavailable P were higher, while the oxidant conditions were lower compared to the other systems. As expected, the soils in CWS and NWS were characterized by the most reduced conditions and by the highest levels of arylsulphatase activity. It was noteworthy that soils in the NWS systems were characterized by the highest level of nonavailable P. Outputs from ecoenzymatic activity confirmed the physico-chemical and biochemical results.

The estimation of the infestation level in a field and the consequent determination of the economic threshold is a basic requisite to rationalize post-emergence weeding. In this study, a simple and inexpensive procedure to determine the economic threshold based on weed cover is proposed. By using high-resolution RGB images captured by a low-cost drone, a free downloadable app for image processing and common spreadsheet software to perform the model parametrization, two different methods have been tested. The first method was based on the joint estimation of the two parameters involved in weed cover calculation, whereas the second method required the availability of further images for the separate estimation of the first parameter. The reliability of the two methods has been evaluated through the comparison with observed data and the goodness of fit in parameter calibration has been verified by calculating appropriate quality indices. The results showed an acceptable estimation of the weed cover value for the second method with respect to observed data (0.24 vs. 0.17 m² and 0.17 vs. 0.14 m², by processing images captured at 10 and 20 m, respectively), whereas the estimations obtained with the first method were disappointing (0.35 vs. 0.17 m² and 0.33 vs. 0.14 m², by processing images captured at 10 and 20 m, respectively).